Robot LIBERO 数据集

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# 文件结构遍历
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with h5py.File(hdf5_file, "r") as f:
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    # Top-level keys (Groups)
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    print(f"\nTop-level keys: {list(f.keys())}")
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    # 类似 posix 方式访问子目录数据
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    agentview_rgb = f["data/demo_0/obs/agentview_rgb"]
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    if isinstance(agentview_rgb, h5py.Group):
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        print("agentview_rgb is a Group, keys:", list(agentview_rgb.keys()))
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    elif isinstance(agentview_rgb, h5py.Dataset):
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        print("agentview_rgb is a Dataset")
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        print(f"  Shape: {agentview_rgb.shape}")
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        print(f"  Dtype: {agentview_rgb.dtype}")
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        print(f"  Size: {agentview_rgb.size}")
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    # read metadata
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    data_attrs = f["data"].attrs
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    print("Data group attributes:")
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    for key in data_attrs.keys():
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        value = data_attrs[key]
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        # Handle bytes/string conversion
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        if isinstance(value, bytes):
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            value = value.decode('utf-8')
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        elif isinstance(value, np.ndarray) and value.dtype.kind == 'S':
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            value = value.tobytes().decode('utf-8')
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        print(f"  {key}: {value}")

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-data/demo_0
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  -actions
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  -dones
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  -obs
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    ---agentview_rgb
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    ---ee_ori
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    ---ee_pos
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    ---ee_states
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    ---eye_in_hand_rgb
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    ---gripper_states
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    ---joint_states
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  -rewards
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  -robot_states
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  -states

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(define (problem LIBERO_Tabletop_Manipulation)
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  (:domain robosuite)
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  (:language Open the middle layer of the drawer)
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    (:regions
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      (plate_region
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          (:target main_table)
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          (:ranges (
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              (0.04 -0.03 0.060000000000000005 -0.01)
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            )
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          )
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      )
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      (akita_black_bowl_region
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          (:target main_table)
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          (:ranges (
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              (-0.09999999999999999 -0.01 -0.08 0.01)
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            )
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          )
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      )
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      (wine_bottle_region
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          (:target main_table)
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          (:ranges (
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              (-0.21000000000000002 -0.060000000000000005 -0.19 -0.04)
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            )
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          )
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      )
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      (cream_cheese_region
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          (:target main_table)
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          (:ranges (
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              (-0.060000000000000005 0.12000000000000001 -0.04 0.14)
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            )
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          )
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      )
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      (stove_front_region
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          (:target main_table)
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          (:ranges (
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              (-0.09 0.16999999999999998 -0.010000000000000002 0.25)
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            )
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          )
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      )
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      (cabinet_region
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          (:target main_table)
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          (:ranges (
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              (0.02 -0.25 0.04 -0.23)
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            )
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          )
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          (:yaw_rotation (
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              (3.141592653589793 3.141592653589793)
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            )
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          )
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      )
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      (stove_region
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          (:target main_table)
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          (:ranges (
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              (-0.42 0.2 -0.4 0.22)
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            )
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          )
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      )
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      (wine_rack_region
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          (:target main_table)
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          (:ranges (
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              (-0.27 -0.27 -0.25 -0.25)
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            )
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          )
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          (:yaw_rotation (
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              (3.141592653589793 3.141592653589793)
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            )
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          )
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      )
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      (top_region
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          (:target wooden_cabinet_1)
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      )
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      (middle_region
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          (:target wooden_cabinet_1)
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      )
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      (bottom_region
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          (:target wooden_cabinet_1)
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      )
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      (top_side
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          (:target wooden_cabinet_1)
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      )
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      (cook_region
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          (:target flat_stove_1)
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      )
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      (right_region
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          (:target bowl_drainer_1)
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      )
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      (left_region
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          (:target bowl_drainer_1)
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      )
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      (top_region
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          (:target wine_rack_1)
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      )
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    )
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  (:fixtures
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    main_table - table
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    wooden_cabinet_1 - wooden_cabinet
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    flat_stove_1 - flat_stove
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    wine_rack_1 - wine_rack
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  )
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  (:objects
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    akita_black_bowl_1 - akita_black_bowl
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    cream_cheese_1 - cream_cheese
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    wine_bottle_1 - wine_bottle
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    plate_1 - plate
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  )
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  (:obj_of_interest
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    wooden_cabinet_1_middle_region
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  )
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  (:init
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    (On wine_bottle_1 main_table_wine_bottle_region)
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    (On akita_black_bowl_1 main_table_akita_black_bowl_region)
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    (On plate_1 main_table_plate_region)
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    (On cream_cheese_1 main_table_cream_cheese_region)
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    (On wooden_cabinet_1 main_table_cabinet_region)
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    (On flat_stove_1 main_table_stove_region)
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    (On wine_rack_1 main_table_wine_rack_region)
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  )
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  (:goal
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    (And (Open wooden_cabinet_1_middle_region))
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  )
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)

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from libero.libero.benchmark import get_benchmark
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import os
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bm = get_benchmark("libero_goal")()
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print(bm.get_task_names())
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print(len(bm.tasks))
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for t in bm.tasks[:5]:
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    print(t.name)
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from libero.libero.envs import OffScreenRenderEnv, DemoRenderEnv
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task = bm.tasks[0]
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print("----")
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print("name:", task.name)
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print("language:", task.language)
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print("problem:", task.problem)
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print("problem_folder:", task.problem_folder)
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print("bddl_file:", task.bddl_file)
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print("init_states_file:", task.init_states_file)
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print("----")
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# For GUI rendering on Mac, use ControlEnv with has_renderer=True
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# DemoRenderEnv uses offscreen rendering (no GUI window)
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#
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# Note: On Mac, if you get OpenGL errors, you may need to:
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# 1. Set environment variable: export PYOPENGL_PLATFORM=osmesa (for headless)
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#    OR use: export PYOPENGL_PLATFORM=glfw (for GUI - requires XQuartz or similar)
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# 2. Install: brew install glfw (if using glfw backend)
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# 3. Alternative: Use OffScreenRenderEnv and visualize frames with matplotlib (see below)
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from libero.libero.envs.env_wrapper import ControlEnv
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env = ControlEnv(
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    bddl_file_name='./libero/libero/bddl_files/libero_goal/open_the_middle_drawer_of_the_cabinet.bddl',
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    camera_names=["agentview"],
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    has_renderer=True,          # Enable GUI window for visualization
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    has_offscreen_renderer=True, # Required for camera observations
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    render_camera="frontview",   # Camera view for rendering
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)
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# Alternative: If GUI doesn't work on Mac, use offscreen rendering and visualize:
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# from libero.libero.envs import OffScreenRenderEnv
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# import matplotlib.pyplot as plt
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# env = OffScreenRenderEnv(
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#     bddl_file_name='./libero/libero/bddl_files/libero_goal/open_the_middle_drawer_of_the_cabinet.bddl',
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#     camera_names=["agentview"],
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# )
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# obs = env.reset()
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# plt.imshow(obs['agentview_image'][::-1])  # Flip vertically for display
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# plt.show()
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obs = env.reset()
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print(obs.keys())
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# Render the environment (this opens the GUI window on Mac)
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# Access the underlying robosuite environment's render method
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env.env.render()
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import numpy as np
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import time
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import h5py
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from libero.libero import get_libero_path
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# Load actions from HDF5 demonstration file
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print("\n" + "=" * 60)
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print("Loading demonstration from HDF5 file...")
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print("=" * 60)
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# Get the demonstration file path for this task
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demo_file_path = os.path.join(
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    get_libero_path("datasets"),
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    bm.get_task_demonstration(0)  # Get demo for task 0
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)
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print(f"Loading demo from: {demo_file_path}")
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# Load actions from HDF5 file
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with h5py.File(demo_file_path, "r") as f:
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    # Get first demo (you can change demo_0 to demo_1, demo_2, etc.)
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    demo_key = "demo_0"
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    actions = f[f"data/{demo_key}/actions"][()]  # Load all actions into memory
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    states = f[f"data/{demo_key}/states"][()]  # Load initial states
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    print(f"Loaded {len(actions)} actions from {demo_key}")
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    print(f"Action shape: {actions.shape}")
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    print(f"Action range: [{actions.min():.4f}, {actions.max():.4f}]")
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    # Optionally set initial state from the demo
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    if len(states) > 0:
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        print(f"Setting initial state from demonstration...")
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        obs = env.set_init_state(states[0])  # set_init_state returns observations
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    else:
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        obs = env.reset()
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# Action format for OSC_POSE: [dx, dy, dz, droll, dpitch, dyaw, gripper]
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# All values are typically in range [-1, 1]
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# - First 3: position delta (translation)
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# - Next 3: orientation delta (rotation)
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# - Last 1: gripper action (-1=close, 1=open)
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print(f"\nReplaying demonstration with {len(actions)} steps...")
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print("=" * 60)
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# Replay the demonstration actions
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print(f"\nReplaying demonstration actions...")
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for t, action in enumerate(actions):
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    # Optionally inject random actions during demo
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    if np.random.random() < 0.1:
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        # Replace with random action
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        action = np.random.uniform(
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            -1,
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            1,
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            size=7
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        )
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        action_type = "random"
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    else:
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        action_type = "demo"
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    obs, reward, done, info = env.step(action)
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    # Render after each step to see the animation
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    env.env.render()
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    # Small delay to make animation visible (adjust speed here)
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    # 0.01 = real-time, 0.05 = slower, 0.001 = faster
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    time.sleep(0.01)
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    # Print progress every 50 steps
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    if (t + 1) % 50 == 0:
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        print(f"Step {t+1}/{len(actions)} ({(t+1)/len(actions)*100:.1f}%)")
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    if done:
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        print(f"\nTask completed at step {t+1}!")
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        break
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print(f"\nDemonstration replay complete!")
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# Close the environment when done
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env.close()